A company hosts a web application on an on-premises server that processes incoming requests. Processing time for each request varies from 5 minutes to 20 minutes. The number of requests is growing. Th

Question

Options

• AConvert the application to a microservices architecture that uses containers. Use Amazon Elastic
• BCreate an Amazon EC2 instance that has sufficient CPU and RAM capacity to run the application.
• CRefactor the web application to use multiple AWS Lambda functions. Use an Amazon API
• DRefactor the web application to use a single AWS Lambda function. Use an Amazon API

• A
  83% (24)
• B
  7% (2)
• C
  7% (2)
• D
  3% (1)

Explanation

AWS Fargate runs containers without managing servers, and ECS Service Auto Scaling adjusts the number of tasks based on demand. Behind an Application Load Balancer, ECS services elastically scale out to handle concurrent long-running requests. This fits workloads with processing times of 5?20 minutes per request. Lambda (C, D) has a maximum 15-minute timeout, so a portion of requests would fail or require complex refactoring and orchestration. Option B relies on vertical scaling and manual intervention, leaving capacity idle and failing to scale automatically with spikes. By containerizing the app and running on ECS with Fargate, the company gains automatic scaling, isolation per task, and no instance management, ensuring reliable throughput as request volume grows while keeping operations minimal.

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